Through this column we have covered many oscillators which are generally very effective in analyzing momentum; they include the Average True Range, MACD and the VIDYA. Some oscillators are better at predicting short term momentum, while some are lagging indicators and tend to shine brighter when it comes to long term momentum. Yet, in this article, I will be focusing on one oscillator—the Aroon Indicator—that has a very different benefit. As a backstory, the Aroon Indicator was developed by Dr. Tushar Chande a little more than 20 years ago. What makes the Aroon indicator special is that it provides in-depth insight as to how the buyers and the sellers are behaving within each price level. I will explain how that understanding of the buyers’ and the sellers’ behavior is very useful information.

Aroon Indicator: The Basics

The Aroon indicator, as seen in the chart below, has two separate curves, in this case marked with green and red. The green curve, called the Aroon Up, measures the buying momentum over time and the red curve, called the Aroon Down, measures the selling momentum. How does the Aroon measure momentum? In the Aroon Up it measures how much time it takes a pair to reach the highest level from the opening price at a given period. Conversely, in the Aroon Down, it measures how much time it takes the pair to reach a new low from the opening price.

In both the Aroon Up and the Aroon Down, the higher the indicator the stronger the momentum. So if the Aroon Up is high, it means buying activity is strong, and if the Aroon Down is high it means selling activity is strong. If both are high, then buying and selling activity is high, and if both are low, vice versa.

Aroon Indicator: Down to Practice

Now that we have established how to read the Aroon Up and the Aroon Down, it’s time to move into practice—how comparing the Aroon Up and the Aroon Down within the Aroon Indicator can help us understand the trend.

In the sample below we can see two zones, which I will call Zone A and Zone B. Each chart variation captures a different layer in the Aroon analysis and therefore each could provide a practical example on how to use the Aroon Indicator.

Zone A.

In Zone A, we can see that, around July(Point X) the EURUSD had just started a very strong bearish trend that subsided only in April 2015. Before the Bearish trend began, the Aroon Up was high and the Aroon Down was low. This indicates that buying activity was elevated while selling activity was low. Then in April, the Aroon Up was starting to fall and the Aroon Down jumped shortly after. What does it mean? It means a quick change of momentum because as soon as the buyers became exhausted the sellers immediately began piling in. Selling activity was high through to April 2015 while buying activity continued to fall.

Insights-

The sellers are substantially more dominant around Point X. The sellers were very quick to react, showing overwhelming conviction over the buyers around this point. Hence, it should be recognized by the trader as a substantial pivot.

Once the Aroon Down jumped it stayed at an elevated level and held almost a straight line, suggesting the selling momentum was especially strong and this means a trader could expect a strong bearish move.

Zone B.

In Zone B, we can see something interesting; while the Aroon Down fell until October 16th, the Aroon Up was still staying low. So, while the sellers were out of the market, the buyers were not coming in, suggesting very weak buying appetite. Moreover, after October 16th, the Aroon Up jumped and so did the Aroon Down; later, both fell and then both jumped again. That suggests that even after the nose dive the pair took, and even after some buyers came back, the buyers were hesitant to buy. Nevertheless, because the Aroon Down is also unstable it means that, at that level, the sellers were also somewhat hesitant.

Insights-

In the immediate time frame, the trader might expect the pair to trade with some sort of sideways momentum, with both the buyers and the sellers undecided.

When we look at the bigger picture and in the context of what happened before October 16th it is clear that the sellers had the upper hand. And, even when the sellers were sitting on the fence, the buyers did not come in and even when they did they were still hesitant. This means that there is a rather high likelihood that the sellers will gradually comeback for more and that signals a high likelihood of another bearish wave once the sideways movement is over.

The Bottom Line

Of course, I always like to stress that no single indicator is perfect and the Aroon Indicator is no different in that respect. If the Aroon Indicator is not calibrated to the right duration or at other times during very high volatility the reliability of it might be lower. But, this is a very powerful Indicator, and the fact that it adds another layer to our analysis by letting us understand the behavior of both the buyers and the seller around each time frame and price zone makes it a powerful tool for those traders that focus on the long term.

A double bottom that fails to hold, resistance that gets sliced in a heartbeat or just a trend that surprisingly breaks. Those are just a few of the”nasty” pitfalls that nearly every trader regularly encounters. Those pitfalls are seemingly out of the blue but are, in fact, just a result of another dimension acting in parallel to the price. That dimension? The money flow. Determining where the money is flowing is exactly what the Accumulation/Distribution Indicator does and does quite well, one might add.

Accumulation/Distribution Indicator: The Basics

The Accumulation/Distribution Indicator, which was developed by Marc Chaikin, was designed to capture the accumulated money flow into an instrument.

The indicator formula factors in for each period (daily, weekly, etc.) the difference in the closing price to the lowest price and to the highest price, and the difference between the instrument’s high and low and, of course, the volume. Moreover, all of the values are accumulated; each reading is added to the last, thus accumulating the values.

The fact that the indicator is built on accumulation allows it to take into account the money flow. That provides the trader with a much clearer glance at the big picture as to how money flows over time in to or out from a pair, rather than just capturing a quick swing as many oscillators do.

The Accumulation/Distribution Indicator does not require any specific parameter; rather, the values are accumulated per candle. For example, if the period is daily, then the indicator accumulates volumes on a daily basis, and so on.

In general, as a rule of thumb, the best periods of the Accumulated/Distribution Indicator are weekly and greater. That’s because, in a daily interval scenario, the volumes can sometimes be irregularly high, often as a result of some short-term, perhaps even insignificant, event. But, for a week to have a high volume, the reason for it has to be much more significant, and that makes the indicator more effective and accurate; the higher you go on the interval, the better the accuracy, and vice versa.

Down to Practice

So, how do we translate the Accumulated/Distribution Indicator into an effective strategy? I find the most practical way to use the indicator is by stretching a trendline below it, and then dividing it into four different signals—Up, Down and Sideways (Up, then Sideways or Down, then Sideways). The Up signal is when the indicator is rising and signals an inflow of funds. The Down is when the indicator is falling and signals an outflow of funds.

In either of the two Sideways signal there is generally a freeze, an indication of low volumes and low activity. The Sideway signal is very important because it usually comes after strong inflows or outflows and it signals the exhaustion of the trend. If an Up signal turns into a Sideways signal, it means money inflows are topping out and money outflows could soon appear. If the Sideways signal comes after a Down signal it could mean that money outflows have been exhausted and money inflows could soon appear.

Now, let’s examine the chart above and see how those signals can help avoid the usual pitfalls.

Resistance-

We can see that during the first Up signal, the pair was heading towards a resistance at Zone A. But what we see is that as the pair headed towards Zone A, our signal below turns from Up to Sideways. This means that, as soon as the pair reached the resistance, the money inflows stopped. The conclusion? The resistance is not likely to break. If the signal would have stayed Up, with the indicator rising, it would mean more money inflows ahead of the resistance, and that could signal a break.

Double Bottom –

In Zone B, we can see the pair has created a double bottom, a classic pattern for a rebound. And yet the Accumulation/Distribution Indicator is still Down. And that means that the double bottom pattern is not strong enough to stop the money outflows and, therefore, might not hold. Seemingly, as long as the signal is still down, the pair could trend higher (slightly) but, overall, the trend is still down, despite the double bottom. While this is not a signal for short sellers to enter into a new short position, it is certainly a signal for buyers to avoid a buy position. That is unless the signal turns Sideways. But, as long as the signal is Down, even if it is at a slower pace, the double bottom is not strong enough for a rebound.

In addition, since it’s usually mentioned in the educational materials, it’s worth mentioning here that if the Accumulation/Distribution Indicator is diverging from the price trend it means that the trend is not reliable. However, usually, the divergence will not be an outright divergence with the indicator moving in the opposite direction to a price, but more of a sideways state while the price continues to move. This, of course, suggests that the trend is weak and might end abruptly.

The Bottom Line

One other issue worth mentioning is that you should check to see if your platform enables you to see volumes on FX pairs, which is a critical component for the Accumulation/Distribution Indicator. But, once the volume is set, the Accumulation/Distribution Indicator can be counted upon and, as can be seen in our sample, can save you from many pitfalls.

Reaching an all-time high in my equity curve means it’s time to buckle down and keep improving. My Dominari strategy has done very well over the past 7 months and especially this and last month.

Is the party going to continue?

I certainly expect so. Drawdowns are inevitable, but that’s part of trading. Short-term performance is exciting, but my ambitious goal is to turn my starting balance of €8,000 into €50,000 within the next 3 years. As of this writing, I’m at €9,323.

You’re probably wondering how a 16% profit leads me to extrapolate an annual return of nearly 100%. The answer is that I dramatically changed my leverage at the end of September… just in time for that ugly drawdown. If I was trading on my current leverage, the current live return would be around 40% (i.e., right on track to hit my goal).

What really counts is what I’ve really done. So far, I’m up €1,323 with another €40,677 to go by December 6, 2019.

The research for Dominari is effectively finished. It’s been slightly more than a year since I began researching the strategy. Although minor variations of Dominari popped up or came from traders copying my signals, none of them improved the long term outcomes.

One version that improved the risk profile was to trade with limit orders. The original blog post mentioned limit orders, but the variation placed them considerably further from the current market than what I tried previously. I also lacked a system for choosing settings appropriate to every pair, which I’ve more than likely resolved. The problem is that I have a million things on my to-do list and only 8 hours a day. You’ll see some of my top projects when you scroll down.

Pilum: The latest and greatest

Pilum is a strategy based on a statistical process that identifies momentum. One of the scary elements about most quantitative strategies is that most of them are mean-reverting. They buy when the price drops and sell when the price rises. The approach is favorable (i.e., profitable) in the long run, but it takes some psychological fortitude to trade.

Pilum is a major advancement because now I’ll have a strategy that should profit exactly when Dominari is most vulnerable to a drawdown.

The new strategy uses limit orders to enter the market. Something like 90% of these orders never execute. But when they do execute, I win 75% of the time. Additionally, my profile of winners to losers is very comfortable.

Most traders understand the ideas even if the statistical jargon is unfamiliar. Pilum’s biggest winner is larger than its biggest loss. The average winner is bigger than the average loser. And, it wins 77% of the time.

So far, I’ve done a sort of piecemeal backtest using R. When I finish the Quantilator (see below), I’ll redo the backtest in a fully fledged trading platform. More than likely, I’ll use QuantConnect to test the strategy level approach.

Trading platforms drive me crazy! The biggest problem that I have as a trader is continuously reallocating capital across my portfolio. MetaTrader, NinjaTrader and the likes implicitly assume that I want to trade some percentage of my account balance on every trade. Either that, or that I trade fixed lots.

Trading that way is extremely inefficient. I’m trying to trade 40+ currencies, so I need to be able to decide which ones need the money for trading and which ones don’t have signals. Then, among the ones that do have signals, I need to dish out their allocations proportionately. The allocations aren’t the same for each instrument. If you know of any good FX platforms that meet this requirement, then let me know in the comments section.

Testing Pilum on its own is important. More important than the performance of Pilum is how that performance interacts with Dominari. That means taking the daily equity values of each currency. Does Dominari lose when Pilum wins and vice versa? Should I allocate capital 50-50 between the strategies or does one strategy deserve the lion’s share of the portfolio? Is one strategy so good that it should get all of the money?

The main concern with portfolio allocation is how it relates to leverage. Dominari historically make 96% annual returns, inclusive of trading costs. But, it’s also trading with leverage of roughly 19:1. It’s possible for markets to rip over stops and create significant losses.

USDCHF lost 40% of its value in one hour in January 2015. Say that the scenario was even more extreme and that nobody could place a trade during that time at any price. That 40% move is multiplied by the 19x leverage used. That’s a theoretical 800% loss; more than the money in the account.

Everyone loves leverage because they think of profits. Leveraging losses is a lot less exciting.

So, if you could earn 96% annual returns and only use 5:1 leverage, that is exponentially superior to earning 96% on 19:1 leverage. I need to compare the returns of Pilum to Dominari per unit of risk. That allows me to do cool things like

Minimize the negative variance of the returns

Increase absolute return

Dynamically increase/decrease strategy allocations if I find patterns in their interactions

It’s a lower tech way of averaging strategies, like the litte guy’s version of what Numerai is doing… except that I have to create all of the strategies myself.

Quantilator

I spent the last few months sending surveys to segments of my subscribers asking how I can better serve you. Articles about indicators are overwhelmingly my most popular content. The trouble with that content is that I can’t complete the research fast enough to keep up.

The most valuable thing I’ve learned from the developing algorithms for the past 11 years is my process of deciding whether or not an indicator offers predictive value.

Say that you’re interested in gaps: do gaps predict future returns? What I normally do is code a gap indicator in R, implement my analysis methodology and give a verdict. My methodology is kind of like a system for building systems. Using my approach usually takes an hour for every new idea that comes along.

An hour is pretty short. An hour is REALLY short compared to when I didn’t have a research methodology. I used to waste months on junk strategies.

With Quantilator, I’ll be able to analyze anything in under 5 minutes. I’ll only have to follow 3 steps:

Run a script in MT4 to export price data and indicator data

Upload the exported data to Quantilator

Analyze the results

This tool will be 100% free. I’m planning to go through the most popular indicators in MetaTrader to analyze whether or not they offer an edge. I’m building a library of small edges that can be combined into powerful strategies like Dominari and Pilum. And, in the spirit of open source, I plan to make that library available to you for free.

I’m writing this tool in Django, which is a Python framework for displaying web content. The initial version will do the analysis. I’m hoping to use this as an education tool. A bit of momentum can justify make it a fully fledged library with sample data, indicators and training videos and more.

Quantilator’s name comes from a key concept in my system analysis methodology; I break data into quantiles. These quantiles calculate average market returns for a given period of time. The quant in Quantilator refers to quantiles, but I really like the implied double entendre of making you a quant. After all, that is what I’m doing for you!

The Moving Average is, perhaps, the most popular indicator in trading for a reason. Comparatively, the crossing average can tell you plenty about a trend, i.e. whether it’s broken or unbroken, changing or holding. But the Moving Average isn’t perfect; there is one area where it falls short and that is volatility. Even an Exponential Moving Average, which places more emphasis on the latest data, can miss the mark when it comes to a sudden change in volatility, rising or falling. Consequently, it can either give a fake signal or else generate a signal only when it is too late to trade on. Volatility is where the Variable Index Dynamic Average comes in, or VIDYA for short.

The Variable Index Dynamic Average or VIDYA was developed by Tushar Chande, and its focus is precisely on volatility. In other words, the VIDYA is an average that adjusts itself to changing volatility. When volatility is high, the VIDYA becomes more sensitive and when volatility is low, the VIDYA becomes less sensitive. That allows you to assess the trend according to current market conditions (and not irrelevant conditions that had earlier prevailed).

The VIDYA in Essence

The math behind the VIDYA formula is quite complicated, but the logic is not.

The VIDYA essentially has two components, the first being the Exponential Moving Average (aka EMA). The second indicator is in the “oscillator family” and it is known as the Chande Momentum Oscillator (aka CMO). Like most oscillators, the Chande Momentum Oscillator generates a signal of -100 and 100, with -100 being oversold and 100 overbought. The EMA is the anchor index, and the CMO’s job is to adjust the exponential average to volatility. The closer the CMO is to 100 or -100 the higher the volatility and the more sensitive our exponential average will turn. Conversely, the closer the CMO is to 0 the less sensitive our exponential average will turn. The final reading after the volatility adjustment is the VIDYA.

As you can see below, once you add the Variable Index Dynamic Average in MetaTrader you get a window with two parameters from which to choose: One is the Period CMO and the other is Period EMA. We can then decide which period the CMO will run on (and thus affect the sensitivity of our EMA) and which period the EMA will run on (to capture our trend). Usually, the best CMO to plug in is a third of the value of the EMA duration; this is to allow the latest change in volatility to impact to the greatest degree. If the CMO period is too long, it will likewise spread over the period too long and consequently fail to reflect current levels of volatility, thus defeating the VIDYA’s purpose.

Comparing the VIDA to the EMA

When we compare the two, we can see the clear advantages the VIDYA(Red) has over the EMA(Green). Both the VIDYA and the EMA run on a 30-week period, but the VIDYA is smoothed out by the Chande Momentum Oscillator running on a 10-week period (again, a third of the whole period). The VIDYA simply captures the trend much more accurately. We can see how, in Point A, when momentum weakens, the Variable Index Dynamic Average starts to flatten, while the EMA just moves across the price and fails to adjust.

This quality is especially beneficial when we want to get an indication if a trend has broken or not. The EMA, in this case, suggests the trend has, indeed, broken but when we look at the VIDYA we quickly get a more accurate picture. We can see that the downtrend has not been broken which allows us to prepare for another bearish round rather than mistakenly expect a rebound.

Of course, for every upside there is a downside and the downside of the VIDYA is that it becomes less effective on a very high duration, such as above 90. The Chande Momentum Oscillator cannot reflect sentiment very well when the duration ןד high and therefore it stops being effective at balancing the Exponential Moving Average within the Variable Index Dynamic Average. One way to tackle or mitigate this is to go higher in the intervals whenever possible, such as from days to weeks or weeks to months. Nonetheless, you should be cognizant of this in inherent weakness in the Variable Index Dynamic Average. Yet, despite that, the Variable Index Dynamic Average does a very effective job. If you are trading under volatile conditions and want to figure out if a trend is broken or set to continue, the Variable Index Dynamic Average could be the solution. When combined with other indicators of momentum, the VIDYA can give you the bigger, clearer picture.